1,722,147 research outputs found
Electrokinetic diffusioosmosis of viscoelastic Phan-Thien-Tanner liquids in slit microchannels
No full textMolecular phylogeny of the spoonbills (Aves: Threskiornithidae) based on mitochondrial DNA
No full textChesser, R. Terry, Yeung, Carol K.L., Yao, Cheng-Te, Tian, Xiu-Hua, Li, Shou-Hsien (2010): Molecular phylogeny of the spoonbills (Aves: Threskiornithidae) based on mitochondrial DNA. Zootaxa 2603 (1): 53-60, DOI: 10.11646/zootaxa.2603.1.2, URL: https://biotaxa.org/Zootaxa/article/view/zootaxa.2603.1.
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Characterization and performance comparison of digital V2-type constant on-time control for buck converters
No full text
Community Embedded Robotics: Vid2Real A Real-World Dataset about Perceived Social Intelligence in Human Robot Encounters
No full textIntroduction
This dataset was gathered during the Vid2Real real-world study as part of the Vid2Real project, which investigates humans’ perception of robots' intelligence in the context of an incidental Human-Robot encounter. The dataset contains (1) participants' questionnaire responses about their experience as pedestrians during an incidental encounter with a robot, as well as (2) data from the robot sensors. In this specific encounter scenario, the robot is trying to enter a building and is asking for help from the pedestrian in two study conditions. The different conditions were manipulated using the robot’s verbal and expressive movement functionalities. This dataset corresponds to the second phase of the Vid2Real project. The dataset from the first phase, namely the Vid2Real online video-based study, was used to design the real-world study and is published in this repository (See .
Dataset Purpose
The dataset includes the participants' responses to validate the hypothesis that robots' social intelligence is positively correlated with human compliance (i.e., humans' willingness to follow robots' orders) in an incidental human-robot encounter context. Further, the sensor data from the robot is provided to facilitate future research in making human-robot encounters fully autonomous.
Dataset Organization
This dataset is about 33 GB in size and has roughly 11.5k files, organized as follows:
The root folder: Vid2RealPhase2_Dataset
HRI relevant data: HumanSubjectsData
Questionnaire used in Phase 2 (Vid2Real_Questionnaire.pdf)
Data Dictionary used in Phase 2 (Vid2RealPhase2_DataDictionary.pdf)
Responses (Vid2RealPhase2_Responses.tab)
Videos of the scene recordings from GoPro (SceneRecordings)
Participant 1 Video (Vid2RealPhase2_P1video.mp4)
Participant 2 Video (Vid2RealPhase2_P2video.mp4)
Participant 3 Video (Vid2RealPhase2_P3video.mp4)
... (25 such videos)
Robot data: RobotData
Participant 1 (Robot_P1)
Raw ROS bagfile (Vid2RealPhase2_P1rosbag.bag)
Robot perspective video (Vid2RealPhase2_robotP1video.mp4)
Sensor calibrations
LIDAR extrinsic matrix (Vid2RealPhase2_P1calib_vlp16_ext.yaml)
IMU extrinsic matrix (Vid2RealPhase2_P1calib_vectornav_ext.yaml)
LIDAR to Camera extrinsic matrix (Vid2RealPhase2_P1calib_vlp16_kinect_ext.yaml)
Camera intrinsic matrix (Vid2RealPhase2_P1calib_kinect_int.yaml)
Velodyne (VLP16) lidar data (Lidar_3d_raw_pc)
First timestep reading (Vid2RealPhase2_P1_vlp16_0001.bin)
Second timestep reading (Vid2RealPhase2_P1_vlp16_0002.bin)
... (many such .bin files)
The timestamps text file (Vid2RealPhase2_P1_vlp16_timestamps.txt)
Inertial measurement unit (IMU) data (Vid2RealPhase2_P1_vectornavIMU.txt)
Camera data, i.e., images that were recorded from the camera on robot
First timestep reading (Vid2RealPhase2_P1_kinect_0001.png)
Second timestep reading (Vid2RealPhase2_P1_kinect_0002.png)
... (many such .png files)
The timestamps text file (Vid2RealPhase2_P1_kinect_timestamps.txt)
Participant 2 (Robot_P2)
Participant 3 (Robot_P3)
... (26 such subfolders)
Data Availability Matrix
The data availability matrix represents the different pieces of robot and human subjects data we provide for each participants. It is summarized as follows:
bagfile: the raw ROS bagfile recording
robot cam video: the video recording obtained from the front Kinect camera on the robot
vlp: extracted binary files for the pointcloud data obtained from VLP16 lidar on the robot
kinect: RGB-images from the Azure Kinect camera in the front of the robot
imu: pose and twist data from the Vectornav IMU sensor on the robot
lidarext: lidar extrinsics w.r.t. robot base
imuext: IMU extrinsics w.r.t. robot base
lidarcamext: extrinsics between the lidar and the camera
camint: camera instrinsics
response: participant responses to the on-site questionnaire
scene video: the video recording obtained from GoPro camera placed at an appropriate distance to record the full human-robot interaction
Due to technical reasons, we were unable to record certain pieces of robot data for a few participant sessions (i.e., 1, 2, 4, 5, 11, 17, 23, 28). Additionally, the robot malfunctioned during the sessions of P13 and P15, therefore, their survey responses were not collected. Lastly, P7 did not consent to be video recorded, but the survey responses were collected. In short, we have 26 valid survey responses and 25 video recordings.
Study Conditions
There are 2 study conditions
Baseline: The robot walks up to the entrance and waits for the pedestrian to
open the door without any additional behaviors. This is also the "control" condition.
Body Language + Verbal: The robot walks up to the entrance, turns its head
to look at the pedestrian and say, "Can you please open the door for me?" and then wait for the pedestrian to open the door.
A between-subject design was adopted to better reflect the nature of real-world scenarios. Participants were randomized to partake in one study condition. After receiving their consent to be part of the study, the participants were instructed to act as pedestrians and walk. After encountering the robot, they could react to it in whatever way they felt natural. In the case where the participants did not help the robot enter the building, the study manager would intervene and help the robot. The study session was considered finished when the robot entered the building. We encourage you to look at the videos in this dataset to understand the study scenario better.
Instruments
The questionnaires used in the study include the Perceived Social Intelligence Scale (PSI), Godspeed Questionnaire, and Anthropomorphism Questionnaire (AMPH). Participant demographic data was also collected. Questionnaire items are attached as part of this dataset.
Human Subjects
Participants were recruited through emails as well as in-person from people who walked by the study site. Among the 26 participants, 13 identified as female and 13 as male; the ages ranged from 18 to 26 (M = 21, SD = 3.01). Their names remained anonymous. Please note that even though the participants' faces are identifiable information, all but one participant agreed to be recorded. Therefore, there are only 25 video recordings in this dataset. Participants were eligible to enter a draw to win a $100 gift card upon study completion. The win rate was approximately 1 in 10. This study was reviewed and approved by UT Austin Internal Review Board.
Robot Data Collection
The dataset contains data about humans’ perceived social intelligence of a Boston Dynamics’ quadruped robot Spot (Explorer model). The robot was selected because quadruped robots are gradually being adopted to provide services such as delivery, surveillance, and rescue. However, there are still issues or obstacles that robots cannot easily overcome by themselves, and they will have to ask for help from nearby humans. Therefore, it is important to understand how humans react to a quadruped robot that they incidentally encounter.
For the purposes of this study, the robot was teleoperated.
We also recorded data from three sensors on the robot :
Lidar: VLP16 Velodyne lidar located at the top of the robot.
Camera: Azure Kinect RGBD Camera located at the front of the robot. However, we only use the RGB channels for this study.
IMU: Vectornav IMU is also located at the top of the robot.
Human Subjects Data Collection
The data was collected through Qualtrics, a survey development platform. After the completion of data collection, the data was downloaded as a CSV file. The participants' ages ranged from 18 to 28 (M = 21, SD = 3.01), and all of them were students at The University of Texas at Austin.
Data Quality Control
For the human subjects data, the Qualtrics platform automatically detects bots, so any response flagged as bots is discarded. All incomplete and duplicate responses were discarded. For the robot data, we provide the raw bagfiles as well as extracted images and pointcloud information. In a second version we will release the sensor calibration files which are needed for correlating data across sensors. The calibration files provide the ‘transformations’ (i.e., distances and orientation information) between the robot base and different sensors on the robot, which will help in sensor fusion and will expand the use of this dataset.
Data Usage
This dataset can be used to conduct a meta-analysis on robots' perceived intelligence. Please note that data is coupled with this study design. The robot data can be used to develop autonomous modules on human-robot encounters.
Acknowledgement
This study was funded through the NSF Award # 2219236GCR: Community-Embedded Robotics: Understanding Sociotechnical Interactions with Long-term Autonomous Deployments.</p
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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